The Federal Aviation Administration (FAA) handles about 45,000 flights a day and that number is only increasing. The FAA predicts a 4.7% annual increase in demand for passenger flights over the next two decades.

This data doesn’t include drones and other unpiloted vehicles.

This is why the FAA is applying new and emerging technologies to understand and make its data more valuable.

In 2008, the FAA and the aviation industry developed the Aviation Safety Information Analysis and Sharing (ASIAS) program. ASIAS has drawn together a wide variety of safety data and information sources across government and industry, including voluntarily provided safety data.

But as the data continues to grow, the FAA and its partners are working together to figure out how to improve how they bring together data to drive decisions, especially those around safety, and to mitigate other risks.

Andy Ho, the senior manager for data and analytics at EY, said the FAA is not alone in this challenge. He said the amount of data every agency is collecting and analyzing means they have to figure out how to manage it all to find value.

“Today, you can use data in general for hindsight, and they call that business intelligence. Everyone’s good at that, whether it’s through an Excel spreadsheet or a dashboard,” Ho said on the discussion Government Modernization Unleashed. “But what’s going to be more important is having foresight. And that foresight really means that you have to look at your data, and training needs to actually have a good picture of what could happen; therefore, machine learning and artificial intelligence can actually capitalize on it, use it and then spit out some of the predictions for you.”

The FAA, for example, not only has to manage the national airspace with traditional airplanes, helicopter and other aircraft, but now drones, air taxis and other growing parts of the system add complexity to the environment.

“The reality is we now have sensors that are capturing data at a much higher atmosphere level. Therefore, there’s just a lot of investment that needs to go into it to account for all the new things that are happening,” he said. “We have people who like to shoot rockets into space, right? We have all the new entrants so, taking that in consideration, you really need to start thinking about how do you want to modernize your data, whether it’s going to be through your people, your process or the technology itself.”

Skillsets, training for the workforce

As agencies evaluate all three of the legs to the data stool—people, process and technology—Ho said the key is to fuse the information across real or potential siloes. The data scientists, engineers and architects play key roles in transforming the data, especially for AI/ML tools to use effectively.

“When you think about the different layers of data there is really the presentation layer, which in the past was Excel spreadsheets where you had to create your macros and then start to put the bar charts in and cut and paste and put it in PowerPoint. Now, individuals are using dashboards. Those dashboards are dynamic as well as they can be fed real time data, or at least near real time,” he said. “That removes the individual from having to curate that data and is actually infusing what we call selection bias. There’re a lot of benefits. There’re many ways that individuals can actually pull the data, manipulate and play with it, as well as visualize it and gain insights for their agency.”

Ho said as the tools continue to evolve as do the workforce and processes surrounding the data.

Increasing need for data readiness

The concept of data readiness is creating taxonomies and ensuring users have faith and trust in the data.

“You have to make sure you continue to put in the right data management principles, the right data strategy in place and then from there really align how your data will accelerate your business goals,” he said. “I think most people really focus on the technology, or just buzzwords we’re using, like AI. But the truth is, there’s a lot that goes into it. That is not the coolest thing to do, but it’s the most important thing to do.”

The other important thing is for agencies to ensure their workforce is trained and has the right skillsets to make the best use of the data and the associated tools.

Ho said leaders have an “obligation” to continually invest in the workforce.

“A leader needs to be able to plan short term and long term. I know that we’re all under pressure to make sure that we fulfill today’s mission, as well as our business plan activities, but truly, ask the question: If in five years I’m not here in this role anymore, am I leaving this place at a better state? So one thing to think about as you deploy data analytics and different types of solutions is, are you putting all your eggs in one basket? Are you depending too much on one type of tool? Is that tool one that everyone knows how to use? Or does it require special training?” he said. “A lot of it is coming back to being sustained, scaled and making sure that you can find people in the future that can continue to work on it. There are a lot of different things to think through, but I would say those are the top three that come to mind, making sure that you build for the future while still maintaining your current present goals.”

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